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We investigate electron transport through an antidot embedded in a narrow strip of two-dimensional topological insulator. We focus on the most generic and experimentally relevant case with broken axial spin symmetry. Spin-non-conservation…

Mesoscale and Nanoscale Physics · Physics 2016-07-19 Alexia Rod , Giacomo Dolcetto , Stephan Rachel , Thomas L. Schmidt

Efficiency of quantum transport through aggregates with multiple end-points or traps proves to be an emergent and a highly non-equilibrium phenomenon. We present a numerically exact approach for computing the emergent time scale and amount…

Quantum Physics · Physics 2025-09-19 Devansh Sharma , Amartya Bose

The anomalous transport and thermodynamic properties in the quantum-critical region, in the cuprates, and in the quasi-two dimensional Fe-based superconductors and heavy-fermion compounds, have the same temperature dependences. This can…

Strongly Correlated Electrons · Physics 2016-07-27 Chandra M. Varma

Superconducting flux qubits are considered to investigate macroscopic many-qubit interactions. Many-qubit states based on current states can be manipulated through the current-phase relation in each superconducting loop. For flux qubit…

Superconductivity · Physics 2012-02-24 Sam Young Cho , Mun Dae Kim

Strongly interacting electron systems can provide insight into quantum many-body phenomena, such as Mott insulating behavior and spin liquidity, facilitating semiconductor optimization. The Fermi-Hubbard model is the prototypical model used…

Mesoscale and Nanoscale Physics · Physics 2024-02-08 Sumedh Vangara

The Hubbard model represents the fundamental model for interacting quantum systems and electronic correlations. Using the two-dimensional half-filled Hubbard model at weak coupling as a testing ground, we perform a comparative study of a…

The non-equilibrium Green's function method combined with density functional theory (NEGF-DFT) provides a rigorous framework for simulating nanoscale electronic transport, but its computational cost scales steeply with system size. Recent…

Mesoscale and Nanoscale Physics · Physics 2025-10-21 Zili Tang , Xiaoxin Xie , Guanwen Yao , Ligong Zhang , Xiaoyan Liu , Xing Zhang , Liu Fei

Quantum transport in a class of nonlinear extensions of the Rudner-Levitov model is numerically studied in this paper. We show that the quantization of the mean displacement, which embodies the quantum coherence and the topological…

Quantum Physics · Physics 2022-05-25 Lei Du , Jin-Hui Wu , M. Artoni , G. C. La Rocca

The Fermi-Hubbard model is a fundamental model in condensed matter physics that describes strongly correlated electrons. On the other hand, quantum computers are emerging as powerful tools for exploring the complex dynamics of these quantum…

Quantum Physics · Physics 2026-05-27 Talal Ahmed Chowdhury , Vladimir Korepin , Vincent R. Pascuzzi , Kwangmin Yu

Quantum transport is ubiquitous in physics. So far, quantum transport between terminals has been extensively studied in solid state systems from the fundamental point of views such as the quantized conductance to the applications to quantum…

Quantum Gases · Physics 2021-12-15 Koki Ono , Toshiya Higomoto , Yugo Saito , Shun Uchino , Yusuke Nishida , Yoshiro Takahashi

In this lecture, we review the experimental situation of heavy Fermions with emphasis on the existence of a quantum phase transition (QPT) and related non-Fermi liquid (NFL) effects. We overview the Kondo lattice model (KLM) which is…

Strongly Correlated Electrons · Physics 2009-09-25 Mireille Lavagna , Catherine Pepin

Quantum computing, a field utilizing the principles of quantum mechanics, promises great advancements across various industries. This survey paper is focused on the burgeoning intersection of quantum computing and intelligent transportation…

Quantum Physics · Physics 2024-06-05 Yifan Zhuang , Talha Azfar , Yinhai Wang , Wei Sun , Xiaokun Cara Wang , Qianwen Vivian Guo , Ruimin Ke

We investigate sequential tunneling transport through a semiconductor double quantum dot structure by combining a simple microscopic quantum confinement model with a Mott-Hubbard type correlation model. We calculate nonperturbatively the…

Mesoscale and Nanoscale Physics · Physics 2009-10-28 R. Kotlyar , S. Das Sarma

State-of-the-art machine learning techniques promise to become a powerful tool in statistical mechanics via their capacity to distinguish different phases of matter in an automated way. Here we demonstrate that convolutional neural networks…

Strongly Correlated Electrons · Physics 2017-08-23 Peter Broecker , Juan Carrasquilla , Roger G. Melko , Simon Trebst

The quantum transport formalism based on tight-binding models is known to be powerful in dealing with a wide range of open physical systems subject to external driving forces but is, at the same time, limited by the memory requirement's…

Mesoscale and Nanoscale Physics · Physics 2012-10-01 Ming-Hao Liu , Klaus Richter

Transport through correlated nanoscale systems underpins the operation of quantum-dot and molecular-scale devices, yet accurate simulations of large open quantum systems remain computationally challenging as system size increases.…

Mesoscale and Nanoscale Physics · Physics 2026-04-09 Maximilian Streitberger , Marko J. Rančić

Advances in cooling and trapping of atoms have enabled unprecedented experimental control of many-body quantum systems. This led to the observation of numerous quantum phenomena, important for fundamental science, indispensable for…

Strongly Correlated Electrons · Physics 2023-07-19 Igor V. Lerner

Entanglement, one of the clearest manifestations of non-classical physics, holds significant promise for technological applications such as more secure communications and faster computations. In this paper we explore the use of…

Quantum Physics · Physics 2024-02-14 Karl Pelka , Matteo Aquilina , André Xuereb

We report a numerical study of transport properties of a quantum dot with superconducting leads. We introduce a general phenomenological model of quantum dot transport, in which electron tunnel rates are computed within the Fermi's Golden…

Condensed Matter · Physics 2009-10-28 C. B. Whan , T. P. Orlando

Optimal Transport (OT) has fueled machine learning (ML) across many domains. When paired data measurements $(\boldsymbol{\mu}, \boldsymbol{\nu})$ are coupled to covariates, a challenging conditional distribution learning setting arises.…